IoT Connectivity Product Lead

Univers combines global operating scale, deep industrial intelligence, and recognition from the institutions shaping energy, technology, and sustainability. The platforms built for the last decade were designed to monitor. Univers was built to act — not just report. Univers operates at global scale: 1,070 GW+ Energy assets under AI management 450M+ Connected sensors and devices 800+ Enterprise customers Leader Gartner Magic Quadrant Leader Home - Univers Job Summary We are seeking a seasoned Product Lead - IoT Connectivity to drive the product strategy, roadmap, and execution of our core IoT Edge-to-Cloud connectivity engine. As a pivotal technical service within our enterprise AI Platform, IoT Connectivity bridges thousands of physical devices, sensors, and edge gateways with our cloud-based analytics and AI Agent ecosystem. In this role, you will lead the product lifecycle for Edge Protocol Conversion, MQTT Broker Infrastructure (EMQX), Offline Data Store-and-Forward and so on. You will define high-throughput and ultra-low-latency data ingestion pipelines that cater to diverse operational scenarios—ensuring robust, reliable, and AI-ready data streams from the physical edge to the AI cloud. Responsibilities: Define and own the product vision, strategy and roadmap for the IoT Connectivity. Establish product metrics covering adoption, reliability, performance, cost and business value. Communicate the platform roadmap and value to senior leadership. Enable other product teams to build and launch AI agents using shared platform capabilities. Protocol Conversion & Adapter Framework: Define product requirements for edge-side multi-protocol conversion (e.g., Modbus, OPC-UA, BACnet, CAN bus, HTTP, CoAP) into standardized MQTT/JSON streams to ensure seamless device interoperability. MQTT Broker & Transmission Engine: Direct the product strategy and feature roadmap for our cloud and edge MQTT messaging infrastructure (built on EMQX), optimizing connection density, message routing, and security policies. Architect product specifications for edge data buffering, localized disk persistence, and intelligent synchronization logic to guarantee zero data loss during network disruptions or intermittent connectivity. Define differentiated transmission strategies balancing High-Throughput / Non-Real-Time bulk telemetry workloads and Ultra-Low Latency / Real-Time critical control or AI inference workflows. Lead the definition and standardization of enterprise-grade Device Data Models, Telemetry Schemas, and Digital Twin representations to convert raw sensor payloads into structured, semantically enriched data. Collaborate closely with AI platform teams to ensure edge metadata, sensor topologies, and telemetry streams are structured for immediate ingestion into real-time AI Agent workflows, RAG pipelines, and time-series engines. Drive product capabilities for remote gateway onboarding, OTA (Over-The-Air) firmware/configuration updates, edge health monitoring, and edge-side containerized deployment. Partner with cloud foundation engineers to ensure the ingress pipeline scales to millions of concurrent device connections with enterprise SLA/HA standards. Serve as the product champion between hardware/embedded engineering, platform infrastructure, AI platform engineers, and industry solution teams. Gather requirements from diverse IoT deployment scenarios (e.g., smart energy, industrial IoT, smart buildings, virtual power plants) to translate field pain points into scalable core product features. Delivery, Reliability and Governance: Own execution from technical discovery and design through development, testing, release, adoption and production operation. Establish engineering planning, architecture governance, software-development lifecycle, quality standards and release practices appropriate for an enterprise platform. Define and operate service-level objectives for availability, latency, freshness, correctness, scalability and recovery; build mature observability, incident-management and continuous- improvement practices. Make security, tenant isolation, identity, policy enforcement, privacy, residency, lineage and audit native capabilities of the platform. Manage technical risk, dependencies, budgets and capacity while communicating progress and trade-offs clearly to executive stakeholders. Customer and Cross-functional Leadership: Engage directly with enterprise customers, operational leaders, IT and data teams, security stakeholders and field engineers to understand real deployment constraints and recurring platform needs. Use selected deployments as design partnerships, turning field learning into reusable platform capabilities and measurable reductions in implementation time. Partner with Engineering Forward Deployed Engineering, Value Engineering and commercial teams on reference architectures, demonstrations, enablement and strategic opportunities. Represent the platform with senior customers and partners, explaining complex technical choices in clear business and operational terms. Qualifications: Education: Bachelor’s or master’s degree in computer science, Electrical Engineering, Internet of Things (IoT), Automation, or a related field. Product Leadership: 6+ years in technical product management (TPM/Product Lead), with a proven track record in IoT platforms, Edge Computing, Industrial IoT (IIoT), or Telemetry Data Ingestion. IoT Protocols: Domain expertise in industrial and IoT communication protocols (Modbus, OPC-UA, BACnet, CAN, MQTT, CoAP, WebSockets, HTTP/REST). MQTT & Ingestion Ecosystem: Strong product familiarity with enterprise MQTT Brokers (EMQX, HiveMQ, AWS IoT Core) and streaming engines (Kafka, EMQX Rule Engine). Edge Resilience: Deep understanding of edge-side store-and-forward mechanisms, local databases (SQLite, LevelDB, TSDB), bandwidth management, and data synchronization strategies. Understanding of agent registries, telemetry, evaluation, governance, observability and platform scalability. Comfortable communicating with senior technical and business stakeholders. Strong interest in agentic AI and enterprise AI platforms.